1 citations · 1 across the 3 of their papers we have counts for
3 papers
Improving Image Clustering with Artifacts Attenuation via Inference-Time Attention Engineering
Kazumoto Nakamura, Yuji Nozawa, Yu-Chieh Lin +2
The goal of this paper is to improve the performance of pretrained Vision Transformer (ViT) models, particularly DINOv2, in image clustering task without requiring re-training or f…
Rethinking Sparse Lexical Representations for Image Retrieval in the Age of Rising Multi-Modal Large Language Models
Kengo Nakata, Daisuke Miyashita, Youyang Ng +2
In this paper, we rethink sparse lexical representations for image retrieval. By utilizing multi-modal large language models (M-LLMs) that support visual prompting, we can extract…
Revisiting a kNN-based Image Classification System with High-capacity Storage
Kengo Nakata, Youyang Ng, Daisuke Miyashita +3
In existing image classification systems that use deep neural networks, the knowledge needed for image classification is implicitly stored in model parameters. If users want to upd…